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Script execution engine for cloud environments.

Project description

CloudRunner.IO Agent tool and API

Copyright (c) 2013-2015 CloudRunner.IO


CloudRunner.IO is a simple yet powerful framework for remote server management. It’s key features include:

  • Execute scripts in your choice(bash, python, ruby, puppet and chef-solo recipes)

  • Pass environment variables between servers and between different script languages (works for a limited number of languages, but can be extended with a plugin)

  • Secure communication using SSL certificates

  • Fast and reliable, using ZeroMQ as a transport backend(although a different backend can be used as a plugin)

  • CloudRunner.IO also offers a commercial server, that performs a lot of useful tasks, including:

    • User management: assign roles for different users on different remote servers(how to impersonate an user on a server)

    • Library management: store, re-use scripts into different kind of stores - GitHub, ButBucket, SVN, Dropbox, Google Drive, Microsoft OneDrive, etc.

    • Workflow management - run multi-step scripts on different servers, with the ability to restart a script from arbitrary step, while keeping the environment context as it was in the first run.

    • Web dashboard for performing different operational tasks and for monitoring latest activities using filters.

    • Execution of scheduled tasks (using Cron)

    • Multi-tenancy - supports isolated group of users who can access servers in a shared environment (including public clouds).

    • HA and Multi-server routing - install master servers in different locations(subnets, public clouds, etc.) and access all your servers from a single access point. No need to attach to different master server to access a remote server into directly inaccessible network. All you need is to allow the master servers to see each other.

    • Highly customizable platform - write your own plugins(in Python) for different kind of workflow management.

    For more details see or ask for details at

Developing CloudRunner

CloudRunner Agent is an open-source project under the Apache 2 license. See the code at Everyone is welcome to contribute.


1. CloudRunner.IO agent

Install and configure the Agent for use with CloudRunner.IO Master server:

pip install cloudrunner
cloudrunner-node configure --org=MY-API-KEY -i NODE_NAME

Note: if NODE_NAME is skipped - the machine hostname will be used instead.

Note: you might need to install some packages before installing with pip. Cloudrunner depends on ZeroMQ, M2Crypto and httplib2. Install them using:

pip install pyzmq
pip install m2crypto
pip install httplib2

Note: Use python2 and pip2(python2-pip) for Arch Linux, CloudRunner only supports Python 2 at the moment, but this will change in future!

You can install them usign pip, but make sure you have already installed:

* C++ compiler: gcc-c++ (CentOS, Fedora) or gcc (Arch Linux) or g++ (Debian, Ubuntu)
* Python Dev libraries: python-devel (CentOS, Fedora) or python2 (Arch Linux) or python-dev (Debian)
* OpenSSL Dev libraries: libssl-dev (Debian) openssl-devel (Centos) or openssl (Arch Linux)
* Swig package (swig) on some Linuxes

2. CloudRunner.IO Python API

To use the Python CloudRunner.IO REST API client - install cloudrunner using pip:

pip install cloudrunner

Instantiate the client object:

from cloudrunner.api.client import *

client = Client('myusername', 'my_api_token')

Now you are ready to load/modify data on the server. Lets start with just listing the repositories in the Library:

repos = client.library.repositories.list() print repos

Returns an array of repositories:

[<cloudrunner.api.library.Repository at 0x7fb4f5e75fd0>,
 <cloudrunner.api.library.Repository at 0x7fb4f6dd7410>,
 <cloudrunner.api.library.Repository at 0x7fb4f5e777d0>,
 <cloudrunner.api.library.Repository at 0x7fb4f5e77890>]

You can use the returned objects and get their properties:

print repos[0].name

>> "RepoName"

Lets see the contents of the root folder in first repo:

print client.library.browser.list(repos[0].name, '/')

[<cloudrunner.api.library.Folder at 0x7f046c81cd90>,
 <cloudrunner.api.library.Script at 0x7f046c81ce10>,
 <cloudrunner.api.library.Script at 0x7f046c81cb90>,
 <cloudrunner.api.library.Script at 0x7f046c81cc10>,
 <cloudrunner.api.library.Script at 0x7f046c81cc50>,
 <cloudrunner.api.library.Script at 0x7f046c81cc90>,
 <cloudrunner.api.library.Script at 0x7f046c81cbd0>]

Now lets make a search for a specific log:

logs ='my favourite pattern')
print logs

Fortunatelly, we get some results:

[<cloudrunner.api.logs.Log at 0x7f046c81cfd0>,
<cloudrunner.api.logs.Log at 0x7f046c81ca10>,
<cloudrunner.api.logs.Log at 0x7f046c81cb10>,
<cloudrunner.api.logs.Log at 0x7f046c81cb50>,
<cloudrunner.api.logs.Log at 0x7f046c81f090>,
<cloudrunner.api.logs.Log at 0x7f046c81f450>]

To retrieve the information for a log, we will load it using:

log = client.logs.get.item(logs[0])
print log

>> <cloudrunner.api.logs.Log object at 0x7f046c7b5310>

To get the runs under a specific workflow in a Log:

print log.workflow[0].runs[0]

<< [<cloudrunner.api.base.ApiObject at 0x7f046c7b5d90>]

print log.workflow[0].runs[0].uuid

<< u'ff57f0b8ac1a426783d5763626be07cb'

We want to see the output from the first run in the first workflow:

logs = client.logs.output.item(l.workflows[0].runs[0].uuid)
print logs

>> [<cloudrunner.api.logs.Log at 0x7f046d08f390>]

print logs[0].screen

>> <cloudrunner.api.base.ApiObject object at 0x7f046c7b5f90>

print logs[0].screen._values

>> {u'NODE_NAME': {u'lines': [[1423063412.399, [u'OUTPUT FROM MY SCRIPT EXECUTION'], u'O']]}}

In fact, we can load the node data directly from the screen object:

print logs[0].screen.NODE_NAME.lines

>> [[1423063412.399, [u'OUTPUT FROM MY SCRIPT EXECUTION'], u'O']]

We can also get the currently registered nodes in our account:

nodes = client.nodes.nodes.list()
print nodes

>> [<cloudrunner.api.nodes.Node at 0x7f8664b10250>,
 <cloudrunner.api.nodes.Node at 0x7f86645151d0>,
 <cloudrunner.api.nodes.Node at 0x7f8664515050>]

node = nodes[0]


print node.meta._values

>> {
     u'ARCH': u'x86_64',
     u'AVAIL_MEM': 767,
     u'CPUS': None,
     u'CPU_CORES': 1,
     u'CRN_VER': u'1.1.0',
     u'DIST': u'CentOS',
     u'HOST': u'NODE_NAME',
     u'ID': u'NODE_NAME',
     u'MASTER_IP': u'',
     u'OS': u'Linux',
     u'PRIVATE_IP': [u'', u''],
     u'PUBLIC_IP': [u''],
     u'RELEASE': u'2.6.32-431.29.2.el6.x86_64',
     u'TOTAL_MEM': 992

print node.joined_at

>> u'2015-01-28 10:39:44'

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